Relating movement primitive length to accuracy in imitation learning

Sterling Holcomb, Rocio Alba-Flores

Research output: Contribution to book or proceedingConference articlepeer-review

Abstract

We present an analysis of the effect of movement primitive length on accuracy using a visual externally observed imitation learning algorithm. Utilizing the noise reduction techniques in the chosen algorithm, we show that, though the largest impact on output path accuracy is the quality of the input data, the inaccuracy of the output increases as the movement primitive length increases as shown by the smoothing spline's sum of squares goodness of fit and the number of data points rejected by the low pass filter.

Original languageEnglish
Title of host publicationIEEE SoutheastCon 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538615393
DOIs
StatePublished - May 10 2017
EventIEEE SoutheastCon 2017 - Charlotte, United States
Duration: Mar 30 2017Apr 2 2017

Publication series

NameConference Proceedings - IEEE SOUTHEASTCON
Volume0
ISSN (Print)1091-0050
ISSN (Electronic)1558-058X

Conference

ConferenceIEEE SoutheastCon 2017
Country/TerritoryUnited States
CityCharlotte
Period03/30/1704/2/17

Scopus Subject Areas

  • Computer Networks and Communications
  • Software
  • Electrical and Electronic Engineering
  • Control and Systems Engineering
  • Signal Processing

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